1. Field of the Invention
The present invention relates to a routing apparatus installed on an autonomous mobile unit.
2. Description of the Related Art
Japanese Patent Application Publication No. 53-16230 describes a vehicle collision avoidance system which detects distance from an obstacle and relative velocity using a radar system. The vehicle collision avoidance system evaluates a risk of collision. When a reflected signal from the obstacle becomes so weak that the obstacle can no longer be detected, the vehicle collision avoidance system estimates the distance from the obstacle and the relative velocity using information obtained so far and evaluates a risk based on the estimation.
Japanese Patent No. 3,866,328 describes an object recognition system which identifies a three-dimensional object around a vehicle based on a distribution of distance to the object, determines relative position of the vehicle and the object, deletes the objects when the relative position falls outside a predetermined range centered on the vehicle, stores any newly detected object, and determines a possibility of collision with the object. Since the object recognition system updates the positions of detected objects as the vehicle travels, an object that is detected multiple times is calculated as multiple objects, limiting movement of the vehicle.
A robot which travels autonomously in an office or home is required to travel without coming into collision with persons. Persons travel slowly, but at uneven speeds. Also, persons tend to stop or change direction suddenly. In such an environment, the robot needs to determine a travel path by avoiding collisions with the persons.
An autonomous mobile unit travels by performing data processing of images appearing in a limited field of view to detect objects, especially persons, around the autonomous mobile unit and correcting its path so as to avoid collision with the persons. The problem here is how to handle a situation in which an object hitherto visible to the autonomous mobile unit goes out of sight. Specifically, as the autonomous mobile unit travels, the field of view sways, causing an object on boundaries of the field of view to go in and out of sight. Also, when the autonomous mobile unit changes courses, the field of view changes as well, which may cause the persons who are hitherto within the field of view disappear from the field of view. Furthermore, due to measurement errors of a sensor which detects objects or due to computational errors in sensor outputs, it may instantaneously become impossible to detect objects. If path computations are performed by deleting data on a person that is out of the field of view, the deleted person may appear in the field of view suddenly at close range when the autonomous mobile unit changes direction again, obstructing smooth travel of the autonomous mobile unit. However, a large storage capacity is needed to continue saving data on out-of-sight objects. Since human motions are erratic, motions of out-of-sight persons cannot be estimated with reliability. Thus, it is important how to handle data on persons that appear and disappear in sight.